np_eig

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and description only states the basic function. Does not disclose behavior for non-square matrices, complex eigenvalues, output ordering, or normalization.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence, 9 words, no redundancy. Perfectly concise for the information provided.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Has output schema (not shown), but description omits return structure detail. Should mention that both eigenvalues and eigenvectors are returned, especially given tool complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Adds 'square' constraint beyond schema's generic array type, clarifying input requirement. Schema coverage is 100% with parameter description, so description adds useful meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clear verb 'compute', specific resources 'eigenvalues and eigenvectors', and condition 'square array'. Distinct from sibling tools like np_det, np_inv, and np_solve.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implied that input must be square, but no explicit guidance on when to use vs alternatives. Lacks context for choosing over similar linear algebra tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.